The aim of research into Knowledge-Based and Intelligent Engineering is to develop systems that replicate the analytical, problem solving and learning capabilities of the brain. These systems bring the benefits of knowledge and intelligence to the solution of complex problems. This international journal provides a forum for publishing the results of recent research into the applications of intelligent systems, and also the tools and techniques necessary for them.

Authors are invited to submit original unpublished work that is not currently under consideration for publication elsewhere, on the following topics:

Abstract: In this paper, a class of stochastic fractional-order fuzzy cellular neural networks with delays are studied. The main objective of this paper is to establish a new set of sufficient conditions, which is for the uniform stability in mean square of such stochastic fractional-order fuzzy cellular neural networks with delays. In particular, the existence and uniqueness of solutions and stability in mean square for a class of stochastic fractional-order fuzzy cellular neural networks with delays are studied by using Banach fixed point principle and stochastic analysis theory, respectively. We have improved and exteded some previous works to some extent,…which are easy to check in practice. One example is given to illustrate the effectiveness of the obtained theory.
Show more

Abstract: Object identification is essential in diverse automated applications such as in health, business, and national security. It relies on the ability of the image processing scheme to detect visual features under a wide variety of conditions such as the object rotation, translation and geometric transformation. Machine learning methods, in this case, play an important role in improving the object identification performance by resolving whether the extracted visual patterns are from the possibly distorted target object or not. In recent works, systems that employ a Convolutional Neural Network (CNN) as the primary pattern recognition scheme demonstrate superior performance over other object…identification systems based on handpicked shape-based features. Several studies credit this to the invariance of CNN to small distortion and spatial translation which in turn is attributed to its filter bank layer or the convolution layer. However, there has been no study to carefully test this claim. Towards studying the source of CNN's superior performance, a methodology is designed that tracks the CNN performance when spatial information for visual features (e.g. edges, corners and end points) are gradually removed. Using the MNIST dataset, results show that as the spatial correlation information among pixels is slowly decreased, the performance of the CNN in recognizing handwritten digits also correspondingly decreases. The drop in accuracy continues until the accuracy approximates the performance of the classifier that was obtained without the filter bank. Conducted using a more complex dataset consisting of images of land vehicles, a similar set of experiments show the same drop in classification performance as spatial information among pixels is slowly removed.
Show more

Abstract: This article proposes a scheme for automatic recognition of Bangla text extracted from outdoor scene images. For extraction, first the headline is obtained, then certain conditions are applied to distinguish between text and non-text. By removing the headline, the Bangla text is partitioned into two zones. Further, an association among the text symbols in these two different zones is observed. For recognition purpose, a decision tree classifier is designed with Multilayer Perceptron (MLP) at leaf nodes. The root node takes into account all possible text symbols. Further nodes highlight distinguishable features and act as a two-class classifiers. Finally, at leaf…nodes, a few text symbols remain, that are recognized using MLP classifiers. The association between the two zones makes recognition simpler and efficient. The classifiers are trained using about 7100 samples of 52 classes. Experiments are performed on 250 images (200 scene images and 50 scanned images).
Show more

Abstract: The Welch algorithm furnishes a good estimate of the spectral power at the expense of high computational complexity. The primary intension is to compute the FFT of the individual non-overlapped parts (i.e., half of the original segments) and acquire the FFT of the overlapped segments by merging those of the non-overlapped segments. In this paper, initially the input discrete signal is subjected to an L / 2-point FFT and then the two successive segments are merged to L-point segment using a modified architecture utilizing an improved Fractional Delay Filter(FDF) design by adapting a Multiplier less implementation for efficient contribution. The…merged segments are then subjected to a window filter, designed using delay lines and shifters replacing the multiplier blocks. Finally the power spectral density (PSD) is computed by computing the periodogram and then averaging the periodogram for the windowed segments. Complete module is realized using Xilinx_ISE software with the target device as xc4vfx100-12-ff1152. The design is coded in verilog HDL. The functional verification of the proposed design reported a PSD with an error of 5.87% when compared with the similar Matlab PSD computation. The synthesis results confirm the efficiency and computational complexity reduction of the proposed architecture when comparing with similar existing researches.
Show more